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All publications by Jun Zhu
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DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics
Yining Wang and Jun Zhu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Max-Margin Majority Voting for Learning from Crowds
Tian Tian and Jun Zhu
Advances in Neural Information Processing Systems 28, 2015


Max-Margin Deep Generative Models
Chongxuan Li, Jun Zhu, Tianlin Shi and Bo Zhang
Advances in Neural Information Processing Systems 28, 2015


Bayesian Max-margin Multi-Task Learning with Data Augmentation
Chengtao Li, Jun Zhu and Jianfei Chen
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Max-Margin Infinite Hidden Markov Models
Aonan Zhang, Jun Zhu and Bo Zhang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Online Bayesian Passive-Aggressive Learning
Tianlin Shi and Jun Zhu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models
Shike Mei, Jun Zhu and Jerry Zhu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Distributed Bayesian Posterior Sampling via Moment Sharing
Minjie Xu, Balaji Lakshminarayanan, Yee W. Teh, Jun Zhu and Bo Zhang
Advances in Neural Information Processing Systems 27, 2014


Spectral Methods for Supervised Topic Models
Yining Wang and Jun Zhu
Advances in Neural Information Processing Systems 27, 2014


Robust Bayesian Max-Margin Clustering
Changyou Chen, Jun Zhu and Xinhua Zhang
Advances in Neural Information Processing Systems 27, 2014


Learning From Weakly Supervised Data by The Expectation Loss SVM (e-SVM) algorithm
Jun Zhu, Junhua Mao and Alan L. Yuille
Advances in Neural Information Processing Systems 27, 2014


Fast Max-Margin Matrix Factorization with Data Augmentation
Minjie Xu, Jun Zhu and Bo Zhang
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Gibbs Max-Margin Topic Models with Fast Sampling Algorithms
Jun Zhu, Ning Chen, Hugh Perkins and Bo Zhang
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Monte Carlo Methods for Maximum Margin Supervised Topic Models
Qixia Jiang, Jun Zhu, Maosong Sun and Eric P. Xing
Advances in Neural Information Processing Systems 25, 2012


Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction
Minjie Xu, Jun Zhu and Bo Zhang
Advances in Neural Information Processing Systems 25, 2012


Max-Margin Nonparametric Latent Feature Models for Link Prediction
Jun Zhu
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Infinite Latent SVM for Classification and Multi-task Learning
Jun Zhu, Ning Chen and Eric P. Xing
Advances in Neural Information Processing Systems 24, 2011


Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines
Jun Zhu, Ning Chen and Eric P. Xing
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Conditional Topic Random Fields
Jun Zhu and Eric P. Xing
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Efficient Relational Learning with Hidden Variable Detection
Ni Lao, Jun Zhu, Liu Xinwang, Yandong Liu and William W. Cohen
Advances in Neural Information Processing Systems 23, 2010


Adaptive Multi-Task Lasso: with Application to eQTL Detection
Seunghak Lee, Jun Zhu and Eric P. Xing
Advances in Neural Information Processing Systems 23, 2010


Predictive Subspace Learning for Multi-view Data: a Large Margin Approach
Ning Chen, Jun Zhu and Eric P. Xing
Advances in Neural Information Processing Systems 23, 2010


Large Margin Learning of Upstream Scene Understanding Models
Jun Zhu, Li-jia Li, Li Fei-fei and Eric P. Xing
Advances in Neural Information Processing Systems 23, 2010


Maximum Entropy Discrimination Markov Networks
Jun Zhu and Eric P. Xing
Journal of Machine Learning Research, 2009


On primal and dual sparsity of Markov networks
Jun Zhu and Eric P. Xing
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


MedLDA: maximum margin supervised topic models for regression and classification
Jun Zhu, Amr Ahmed and Eric P. Xing
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction
Jun Zhu, Zaiqing Nie, Bo Zhang and Ji-rong Wen
Journal of Machine Learning Research, 2008


Laplace maximum margin Markov networks
Jun Zhu, Eric P. Xing and Bo Zhang
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Partially Observed Maximum Entropy Discrimination Markov Networks
Jun Zhu, Eric P. Xing and Bo Zhang
Advances in Neural Information Processing Systems 21, 2008


Dynamic hierarchical Markov random fields and their application to web data extraction
Jun Zhu, Zaiqing Nie, Bo Zhang and Ji-rong Wen
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


2D Conditional Random Fields for Web information extraction
Jun Zhu, Zaiqing Nie, Ji-rong Wen, Bo Zhang and Wei-ying Ma
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005